Continuous analysis of dissolved gaseous mercury (DGM) and mercury flux in two freshwater lakes in Kejimkujik Park, Nova Scotia: Evaluating mercury flux models with quantitative data
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O'Driscoll, NJ
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机构:Univ Ottawa, Fac Sci, Dept Biol, Ottawa, ON K1N 6N5, Canada
O'Driscoll, NJ
Beauchamp, S
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机构:Univ Ottawa, Fac Sci, Dept Biol, Ottawa, ON K1N 6N5, Canada
Beauchamp, S
Siciliano, SD
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机构:Univ Ottawa, Fac Sci, Dept Biol, Ottawa, ON K1N 6N5, Canada
Siciliano, SD
Rencz, AN
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机构:Univ Ottawa, Fac Sci, Dept Biol, Ottawa, ON K1N 6N5, Canada
Rencz, AN
Lean, DRS
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机构:Univ Ottawa, Fac Sci, Dept Biol, Ottawa, ON K1N 6N5, Canada
Lean, DRS
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[1] Univ Ottawa, Fac Sci, Dept Biol, Ottawa, ON K1N 6N5, Canada
Diurnal patterns for dissolved gaseous mercury (DGM) concentration, mercury flux, several water variables (pH, oxidation reduction potential (ORP), water temperature), and meteorological variables (wind speed, air temperature, % relative humidity, solar radiation) were measured in two lakes with contrasting dissolved organic carbon (DOC) concentrations in Kejimkujik Park, Nova Scotia. A continuous analysis system made it possible to measure quick changes in DGM over time. Consistently higher DGM concentrations were found in the high DOC lake as compared to the low DOC lake. An examination of current mercury flux models using this quantitative data indicated some good correlations between the data and predicted flux (r ranging from 0.27 to 0.83) but generally poor fit (standard deviation of residuals ranging from 0.97 to 3.38). Cross-correlation analysis indicated that DGM dynamics changed in response to solar radiation with lag-times of 65 and 90 min. This relationship with solar radiation was used to develop new predictive models of DGM and mercury flux dynamics for each lake. We suggest that a generalized approach using time-shifted solar radiation data to predict DGM can be incorporated into existing mercury flux models. It is clear from the work presented that DOC and wind speed may also play important roles in DGM and mercury flux dynamics, and these roles have not been adequately accounted for in current predictive models.